Harnham
SEARCH
Shortlist

SAS Jobs in New York

Search for our latest SAS Jobs based in New York, apply online today here.

Latest Jobs

Media Analytics Manager
Salary

US$120000 - US$130000 per annum

Location

Boston, Massachusetts

Description

Do you have a background in media and have proven commercial experience extracting insights from media mix and/or marketing mix models?

ADD TO SHORTLIST
Senior Manager, Competitive Intelligence
Salary

US$140000 - US$150000 per annum

Location

Boston, Massachusetts

Description

A global leader in Biotechnology is looking to add a Competitive Intelligence professional to their Strategic Analytics & Insight team!

ADD TO SHORTLIST
SVP, Marketing Sciences
Salary

US$250000 - US$270000 per annum

Location

New York

Description

A top organization within the Ad Measurement and Attribution space is looking to add a seasoned leader to their rapidly scaling team!

ADD TO SHORTLIST
VP, Advanced Analytics & Data Science
Salary

US$225000 - US$245000 per annum

Location

New York

Description

Are you an all-encompassing Advanced Analytics Leader who remains hands-on in using Python and/or R to develop predictive models?

ADD TO SHORTLIST
Manager, Data Science & Marketing Analytics
Salary

US$150000 - US$160000 per annum

Location

New York

Description

Do you have strong proficiency in Python and have experience working for eCommerce/internet companies?

ADD TO SHORTLIST
Consumer Insights Analyst
Salary

US$70000 - US$75000 per annum

Location

Boston, Massachusetts

Description

Do you have proven commercial analytics experience working at CPG, retail, and/or eCommerce companies?

ADD TO SHORTLIST
Manager, Marketing & Customer Analytics
Salary

US$120000 - US$140000 per annum

Location

Boston, Massachusetts

Description

We are working with one of the most unique eCommerce brands that has exploded since the early 2000s. Apply today to be a part of a global impact!

ADD TO SHORTLIST
Vice President of Analytics
Salary

US$150000 - US$170000 per annum

Location

New York

Description

We are working with a fast-paced and rapidly expanding media company looking to optimize their data and take their analytics function to the next level.

ADD TO SHORTLIST
Technical Product Manager, Machine Learning
Salary

US$130000 - US$140000 per annum

Location

Boston, Massachusetts

Description

Do you have product management experience in a SaaS and/or internet environment and have experience leveraging machine learning algorithms/models?

ADD TO SHORTLIST
Director, Data Science & Marketing Analytics
Salary

US$230000 - US$250000 per annum

Location

Boston, Massachusetts

Description

Do you have proven commercial experience managing analytics teams at top internet and/or eCommerce companies?

ADD TO SHORTLIST
Manager, Data Science - Omnichannel
Salary

US$140000 - US$160000 per annum

Location

New York

Description

Do you have a background in retail/eCommerce and have strong statistical modeling experience using Python?

ADD TO SHORTLIST
Product Manager (Data Science)
Salary

US$125000 - US$135000 per annum

Location

Boston, Massachusetts

Description

Are you a Product Manager who is proficient in Python and have experience leveraging machine learning models?

ADD TO SHORTLIST

Harnham blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

Visit our Blogs & News portal or check out our recent posts below.

Zoom Fashion: Five Marketing Insights From A Remote World

Remember Fashion Week? That place where Designers shared their imagination on stage, and models wore outfits which seemed out of this world. Remember the mall? That place where you found clothes to make you stand out as an individual in your surroundings. Now that we’ve been quarantined and social distanced for a year, and our office is our living room, fashion doesn’t play so much into our daily lives. Or does it? Sure, it’s had to change just like we have. Actually, it’s because we’ve changed. Where once consumers followed fashion, now fashion follows the consumer. From the Digital Transformation with AI to the call for comfort, the fashion season has changed. Here are a few insights as to how. Five Marketing Insights on the Future of Fashion Demand Is Down  Whether you work from home or at a remote location, the rules of office fashion have changed. So has formal wear fashion for that matter. With no events to attend, no weddings in play, and most restaurants closed, the need for clothes to wear for specific outings have fallen out of favor.  Add in a mix of unemployment and slowed spending – choices focused on food and rent versus clothing, footwear, and accessories, and the fate of fashion seemed completely downgraded. But companies with a conscience, and those focused on leisure and activewear, have an opportunity to bounce back. Consumers working from home are focused on casual for business, and comfort for consumers interested in health and wellbeing. Digital Is Up Online sales, virtual customer service, and digital transformation of the retail industry have bloomed within just a few months. Shopping is social and brands have had to keep up.Since the debut of finding fashion fits in a videogame-like format which allows you to virtually try on different styles of clothing, haircuts, shoes, or design your own accessories, fashion has gained ground in VR. Though brick-and-mortar stores aren’t out of the game yet, online sales will reign. Fashion brands are finding ways to adapt and balance the needs of their consumer from a mix of online, virtual experiences with a human touch. Classic Comfort Whether we’re in bunny slippers, slipper socks, or bare feet as we pad across the living room to our computer, we can feel a little childish glee that slippers are estimated to grove 50% or more this year. Add in our most comfortable set of lounge pants, and all we have to worry about is a top that seems business-y enough for our Zoom meetings, right? Though the pandemic has escalated consumer desires for comfort and casual wear, most were already in the mindset – even before work from home and remote working became the new normal. However, with the consumer mindset focused on form and function versus the latest and greatest, much of the fashion industry has faced major overstock issues. Consumers now want clothing that’s better made, lasts longer, and is more sustainable. These new consumer demands and facing overstock issues have forced brands to improve Insight Analytics for the industry. Social Justice Is On The Line Brands who focus first on their employees and vendors are more likely to win the hearts of today’s consumer. Shopping is still social. But now it comes with a social justice impetus to pay workers fairly for their work as they learn about pay structures or lack thereof for garment workers and sales assistants.  Ultimately, consumers are calling for authenticity and transparency. Brands who engage authentically at every level of their logistics and supply chain, could more easily find common ground and a boon of support from shoppers for showing they care. AI-Focused Fashion Gains Ground AI and Machine Learning are helping brands at scale and offering consumers a unique virtual experience. From chatbots to smart image recognition systems, AI is transforming the industry at every level – manufacturing to quality assurance to design and Marketing and sales. Outside the making of the products, AI is facilitating change and improving the shopping experience. Using Predictive Analytics, Advanced Analytics, and intelligent automation, it is improving the efficiency of the consumer’s journey.  Though fashion has definitively shifted online, that doesn’t mean there’s no room at the table for brick-and-mortar space. Opportunities exist for a blend of digital, pop-ups, and temporary locations so brands can expand their reach at every place consumer’s might prefer to shop. But in the digital space, ecommerce and mobile apps are a focus for consumers and fashion brands alike as it offers a ‘try before you buy’ within a virtual medium. If you’re interested in Big Data & Analytics, Advanced Analytics, Life Sciences, Data Science, or any of our Data professional fields, we may have a role for you. Check out our current vacancies or contact one of our expert consultants to learn more.  For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.  For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Jenni Kavanagh

Jenni Kavanagh

11. March 2021

Why You Should Always Be Learning In Data Science: Tips From Kevin Tran

Last month we sat down with Kevin Tran, a Senior Data Scientist at Stanford University, to chat about Data Science trends, improvements in the industry, and his top tips for success in the market.  As one of LinkedIn’s Top Voices of 2019 within Data & Analytics. his thoughts on the industry regularly garner hundreds of responses, with debates and discussions bubbling up in the comments from colleagues eager to offer their input.  This online reputation has allowed him to make a name for himself, building out his own little corner of the internet with his expertise. But for Tran, it’s never been about popularity. “It’s not about the numbers,” he says without hesitation. “I don’t care about posting things just to see the number of likes go up.” His goal is always connection, to speak with others and learn from them while teaching from his own background. He’s got plenty of stories from his own experiences. For him, sharing is a powerful way to lead others down a path he himself is still discovering.  When asked about the most important lesson he’s learned in the industry, he says it all boils down to staying open to new ideas.  “You have to continue to learn, and you have to learn how to learn. If you stop learning, you’ll become obsolete pretty soon, particularly in Data Science. These technologies are evolving every day. Syntax changes, model frameworks change, and you have to constantly keep yourself updated.”  He believes that one of the best ways to do that is through open discussion. His process is to share in order to help others. When he has a realisation, he wants to set it in front of others to pass along what he’s learned; he wants to see how others react to the same problem, if they agree or see a different angle. It’s vital to consider what you needed to know at that stage. Additionally, this exchange of ideas allows Tran to learn from how others tackle the same problems, as well as get a glimpse into other challenges he may have not yet encountered.  “When I mentor people, I’m still learning, myself,” Tran confesses. “There’s so much out there to learn, you can’t know it all. Data Science is so broad." At the end of the day, it all comes down to helping each other and bringing humanity back to the forefront. In fact, this was his biggest advice for both how to improve the industry and how to succeed in it. It’s a point he comes back to with some regularity in his writing. “It doesn’t matter how smart you are, stay humble and respect everyone,” one post reads. “Everyone can teach you something you don’t know.” Treating people well, understanding their needs, and consciously working to see them as people instead of numbers or titles—this, Tran argues, is how you succeed in the business. To learn and grow, you must work with people, especially people with different skills and mindsets. Navigating your career is not all technical, even in the world of Data. “The thing that cannot be automated is having a heart,” he tells me sagely. Beyond this, Tran stresses the need for a solid foundation. The one thing you can’t afford to do is take shortcuts. You have to learn the practicalities and how to apply them, but to be strong in theory as well.  Understanding what is happening underneath the code will keep you moving forward. He compares knowing the tools to learning math with a calculator. “If you take the calculator away, you still need to be able to do the work. You need the underlying skills too, so that when you’re in a situation without the calculator, you can still provide solutions.” By constantly striving to collaborate and improve, Tran believes the Data industry has the best chance of innovating successfully.  If you’re looking for a new challenge in an innovative and collaborative environment, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

William Reichert

William Reichert

19. March 2020

Recently Viewed jobs